Yu Tong - Recent progress in Hamiltonian learning - IPAM at UCLA Published 2023-10-02 Download video MP4 360p Download video MP4 720p Recommendations 52:22 Kianna Wan - Fast multipole method on a quantum computer - IPAM at UCLA 50:26 Tom Goldstein: "What do neural loss surfaces look like?" 52:45 Ryan Babbush - Searching for valuable applications of fault-tolerant quantum computers in chemistry 47:51 Terence Tao: Structure and Randomness in the Prime Numbers, UCLA 1:04:48 Stéphane Mallat: "Scattering Invariant Deep Networks for Classification, Pt. 1" 40:08 The Most Important Algorithm in Machine Learning 1:01:50 Iain Murray: "Introduction to MCMC for Deep Learning" 1:05:04 Terence Tao: Nilsequences and the Primes, UCLA 42:05 Michael Elad: "Sparse Modeling in Image Processing and Deep Learning" 56:16 Judea Pearl Tribute Symposium: Causality 1:06:28 Data-driven MPC: From linear to nonlinear systems with guarantees 13:03 Does Hollywood ruin books? - Numberphile 30:27 The Traveling Salesman Problem: When Good Enough Beats Perfect 50:06 Maziar Raissi: "Hidden Physics Models: Machine Learning of Non-Linear Partial Differential Equat..." 1:16:17 Terence Tao: The Cosmic Distance Ladder, UCLA 1:03:05 A Path Towards Autonomous Machine Intelligence with Dr. Yann LeCun 1:12:03 Steve Brunton: "Introduction to Fluid Mechanics" 49:01 James Zou: "Deep learning for genomics: Introduction and examples" 1:16:34 Steve Brunton: "Dynamical Systems (Part 2/2)" 40:40 Mamba: Linear-Time Sequence Modeling with Selective State Spaces (Paper Explained) Similar videos 49:22 Yu Tong: Recent progress in Hamiltonian learning 1:06:08 Yu Tong - The Heisenberg limit and early fault-tolerant quantum algorithms, part 1/2 - IPAM at UCLA 51:58 Di Fang - Numerical Analysis for Hamiltonian Simulation and Hamiltonian Learning - IPAM at UCLA 32:48 Yu Tong - Heisenberg-limited ground state energy estimation & early fault-tolerant quantum computers 48:37 Di Fang - Time-marching strategy can work quantumly for differential equations - IPAM at UCLA 48:54 Anthony (Chi-Fang) Chen - “Quantum” Markov Chain Monte Carlo algorithm - IPAM at UCLA 54:27 Lin Lin - Single-ancilla ground state preparation via Lindbladians - IPAM at UCLA 1:04:41 Quantum Linear Algebra With Near-Optimal Complexities 54:10 Quantum Algorithms for Eigenvalue Problems - Lin Lin 28:34 QIP2023 | Entanglement area law for 1D gauge theories and bosonic systems (Nathan Wiebe) 27:59 QIP2023 | Learning many-body Hamiltonians with Heisenberg-limited scaling (Hsin-Yuan Huang) 1:16:07 Lin Lin - A mathematical introduction to quantum embedding theory - IPAM at UCLA 24:13 QIP2023 | Classical shadows of fermions with particle number symmetry (Guang Hao Low) 45:46 Jianfeng Lu: "PDE analysis for sampling dynamics and generative models" 53:01 Konstantina Trivisa - Efficient Quantum algorithms for linear and non-linear differential equations 34:15 Andras Gilyen: On preparing ground states of gapped Hamiltonians 19:41 Effective Hamiltonian of exact half filling Hubbard model 25:58 Going beyond the scale: Uniform observable error bounds for Trotter formulae - Di Fang | TQC 2023 21:00 QCTIP2020 - Yuan Su More results